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Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants' air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into simulations, in order to improve the prediction performance of AC energy consumption. Based on long-term onsite monitoring of household thermal environments and AC usage patterns, two stochastic models were built using unsupervised cluster and statistical methods. Based on the Monte Carlo method, the AC operation schedule was generated through AC opening duration, setpoints, and other relevant parameters, and was further incorporated into EnergyPlus. The results show that the ideally deterministic AC operation settings from the standard significantly overestimate the cooling energy consumption, where the value based on the fixed mode was 6.35 times higher. The distribution of daily AC energy consumption based on the stochastic modeling was highly consistent with the actual situation, thanks to the accurate prediction of the randomness and dynamics of residents' AC usage patterns. The total cooling energy consumption based on two stochastic models was found to be much closer to the actual values. The work proposes a method of embedding stochastic AC usage models to EnergyPlus 22.1 benefits for an improvement in building energy consumption simulation and the energy efficiency evaluation regarding occupant behavior in the future. [ABSTRACT FROM AUTHOR]

We conducted anchoring performance, stress distribution, and full-scale indoor pulling tests on glass-fiber-reinforced polymer (GFRP) bolts. The tests were conducted using finite element software while considering the multi-interface contact and BK criterion by using the cohesive element to simulate the contact relations between the anchor rod body and concrete and building an axial symmetry calculation model of the GRFP bolt and concrete. The results indicated that the finite element model based on cohesive element accurately represents the load–displacement relationship of the GFRP bolt and the distribution law of axial stress along the anchoring length. In addition, the simulation outcomes of the load–displacement relationship were in good agreement with the measured test values. Under the same load, the axial-force-transferred depth of the bolt body was identical regardless of the anchorage length. As anchoring length increases, the pull load on the bolt and the decay rate of axial stress along the anchoring length rises gradually. There is a critical value for the anchorage length of the bolt. [ABSTRACT FROM AUTHOR]